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智慧道路——2023年路肩識別行業報告
市場調查報告書
商品編碼
1337766

智慧道路——2023年路肩識別行業報告

Smart Road - Roadside Perception Industry Report, 2023
出版日期: | 出版商: ResearchInChina | 英文 350 Pages | 商品交期: 最快1-2個工作天內

價格
簡介目錄

基於路肩識別，路肩識別解決方案提供商正在向智能交通行業拓展。

智能路肩識別的最終目標是服務人們，提升人們的體驗。 出於成本原因，目前的道路感知硬件部署不需要覆蓋所有道路，從重點路段、關鍵場景開始，逐步擴展到更多智慧路段。

部署多台路側識別硬件設備，打通路側識別產業鏈。 很多路側識別解決方案集成商都採用了這種模式，Huawei就是一個典型的例子。 Huawei已完成路側識別硬件、計算單元、通信單元、綜合解決方案的全面佈局。

激光雷達在路邊優勢明顯。 但其成本較高，難以在路邊大規模使用。 因此，降低路邊激光雷達的應用成本是激光雷達供應商的首要任務。

高分辨率激光雷達具有更好的檢測範圍和檢測到的物體數量。 例如，300通道激光雷達的探測範圍為150米，而32通道激光雷達只能探測50米左右。

Falcon AI是2022年底推出的一款集成超遠距離AI激光雷達，主要針對車路協同和智慧高速公路場景，最大探測距離為500m。 它集成高計算GPU模塊，支持各種深度學習算法，可顯著降低邊緣計算配置要求和系統部署複雜度。

本報告審視了全球路邊識別行業，並提供了市場概況，包括關鍵技術和發展趨勢、實施示例以及進入市場的公司概況。

目錄

第一章路肩識別現狀

  • 自動駕駛對路肩識別的要求
  • 路邊意識培養的政策和標準
  • 智能路邊識別市場規模
  • 智能路側識別產業鍊格局
  • 路側識別商業模式探索

第二章路側識別主要技術及發展趨勢

  • 路肩識別主要技術及施工難點
  • 激光雷達技術
  • 雷達技術
  • 路邊攝像頭
  • 發展趨勢一：多傳感器感知融合
  • 發展趨勢二：全息、世界感知平台

第三章路邊識別實現示例

  • 探索路肩識別應用場景
  • 智慧高速公路路肩識別應用實例
  • 智慧路口路肩識別應用實例
  • 智能公交路側識別應用實例

第四章路側識別系統集成商

  • 路邊識別解決方案提供商業務概況
  • VanJee Technology路肩識別解決方案概述
  • Huawei
  • Baidu
  • TransInfo Technology
  • Dahua Technology
  • Hikailink
  • Hualu Yiyun
  • Gosuncn
  • ZTE
  • VanJee Technology
  • CiDi (Changsha Intelligent Driving Institute) Ltd
  • NEBULA LINK
  • Hikvision
  • JueFX Technology
  • LiangDao Intelligence
  • Institute of Deep Perception Technology
  • OriginalTek

第五章路側識別設備供應商

  • ZTITS
  • Uniview Technologies
  • Hurys
  • Sinoits
  • DeGuRoon
  • Raysun
  • TransMicrowave
  • Muniu Technology
  • HawkEye Technology
  • SONDIT
  • RACO Defense
  • Nanoradar
  • LeiShen Intelligent System
  • RoboSense
  • SMiTSense
  • Benewake
  • Neuvition Technology
  • 其他
簡介目錄
Product Code: ZHP131

Roadside perception research: evolution to integration, high performance and cost control.

In June 2023, at a regular policy briefing of the State Council the Ministry of Industry and Information Technology of China (MIIT) pointed out that the state will still adhere to the "vehicle-energy-road-cloud" integrated development, further improve connectivity infrastructures, and accelerate the construction of infrastructures for C-V2X, roadside perception and edge computing.

In addition, the gradual implementation of the standards concerning roadside perception facilitates the steady and orderly development of the whole industry:

  • In May 2023, the "Roadside Sensing System for Vehicle Infrastructure Cooperative System-Part 1: Technical Requirements" and the "Roadside Sensing System for Vehicle Infrastructure Cooperative System-Part 2: Test Methods", two standards Beijing Baidu Zhixing Technology Co., Ltd. took the lead in formulating, was drafted for comments.
  • In June 2023, the CVIS Roadside Infrastructure-Technical Requirements and Test Methods for LiDAR was filed and reviewed, and officially fit into in the standard development plan of the China Society of Automotive Engineers, with the drafting task being No.2023-029. The standard was jointly initiated by Beijing Baidu Zhixing Technology Co., Ltd., Beijing Chewang Technology Development Co., Ltd. (BJCW) and Hesai Technology Co., Ltd.

Based on roadside perception, roadside perception solution providers extend upward to the intelligent transportation industry.

The ultimate goal of roadside perception of smart roads is to serve people and enhance experience. For cost reasons, the current deployment of roadside perception hardware does not need to cover all roads, but starts from key sections and key scenarios, and then gradually expands to a larger number of smart road sections.

By business layout, roadside perception solution integrators can be roughly divided into two types:

  • Deploy some roadside perception hardware devices by themselves to open up the roadside perception industry chain. Most of the roadside perception solution integrators in the industry adopt this model, and Huawei is the most typical one. Huawei has completed the comprehensive layout of roadside perception hardware, computing units, communication units and integrated solutions;
  • Rely on roadside perception hardware from ecosystem partners. Those that underline ecosystem cooperation and remain weak in hardware deployment adopt this model, and Baidu is the most typical one. Baidu concentrates on developing integrated solutions and system architectures, while its roadside hardware is largely supplied by its partners.

Huawei

In 2023, Huawei introduced the "1000m Global Radar-Video Fitting and Shooting Solution" suitable for highway scenarios. With the multi-dimensional perceptual fusion technology based on video and radar, the solution enables accurate collection of the road network traffic information, and real-time acquisition of dynamic and static traffic data. It allows for structured analysis and fitting of the collected data via ITS800, the intelligent transportation edge hardware. Combined with HD maps, it can also realize round-the-clock perception, high-precision detection and low-cost deployment (reducing a large number of poles).

Baidu

In May 2023, Baidu announced the "Zhilu OS 1.0". Driven by high-level autonomous driving technology and application, it is a basic software platform for intelligent connected roadside computing units under the overall architecture of China's vehicle-road-cloud integrated solutions. It can provide complete vehicle-road-cloud integrated development environments, frameworks and application examples, helping intelligent transportation system integrators, automakers and autonomous driving technical solution providers among others to easily build CVIS-based autonomous driving systems and intelligent transportation applications from 0 to 1.

Roadside perception hardware evolves to high performance and cost control.

As an underlying basic technology, intelligent roadside perception plays a crucial part in the development of intelligent transportation/smart roads. Roadside perception hardware mainly includes camera, radar, LiDAR, and radar-video all-in-one. At present, single roadside perception hardware fails to meet the requirements of smart roads, while multi-sensor fusion is a development trend of roadside perception. The whole roadside perception hardware market is heading in the direction of high performance and cost reduction.

Integration

From the roadside perception market in 2023, it can be seen that both roadside video-only devices and radar-video all-in-ones tend to be integrated in appearance, becoming diversified, not limited to conventional forms like gun, cuboid and sphere.

Huawei

In March 2023, Huawei launched a stereo event radar-video all-in-one, a device equipped with two 8-megapixel cameras and radar. With the built-in 4T computing power supporting radar-video fitting algorithms, it integrates video and radar perception through the long- and short-focus relay lenses to perceive the entire tunnel, hereby effectively solving the problem of multiple sensors and difficult connection in the tunnel.

Sinoits

In April 2023, Sinoits unveiled Atongmu, its self-developed dual-spectrum radar-video all-in-one that uses infrared thermal imaging and visible light to collect videos. Integrating radar traffic analysis technology, it can accurately detect the position, speed and other information of objects, without being intervened by weather. This new cost-effective product works around the clock and features wide coverage and high accuracy. It is free of light, day and night, fog or rain. It requires lower additional deployment cost and low maintenance cost, and offers high reliability.

SMiTSense

In June 2023, SMiTSense introduced a 3D radar-video all-in-one, a device which combines the radar-video fusion algorithm with the radar-video fusion sensor for software-hardware co-optimization. It performs spatial matching and time synchronization of the 3D point cloud of the LiDAR and the 2D color image of the camera. With high object recognition accuracy, it can be used widely in intelligent transportation, for example, holographic tunnel, blind spot warning, overspeed warning, signal violation detection, and illegal road occupation.

4D radar

Radar is conventional hardware for roadside perception. In recent years, roadside vendors have started exploring the application of 4D radar to roadside. Among the mainstream roadside perception hardware suppliers, Raysun, DeGuRoon and HURYS have launched their 4D radar products.

DeGuRoon

"CitRadar-4DIR600", a 4D imaging radar revealed in March 2023, adopts a multi-beam time-sharing mode and intelligent MIMO virtual aperture synthesis technology, with the overall performance 64 times higher than conventional radars. The powerful data processing capability enables the radar to track up to 1,000 structured objects and support the data output in a 600m range.

HURYS

In July 2022, HURYS launched RTE V29 microwave detector, a brand-new roadside 4D radar. Leveraging the self-developed 4D radar front-end and industry's leading algorithm, it perceives all participants in various traffic environments and accurately scans the profile height of objects, and empowers the high-precision holographic perception of intersections and road sections with high detection accuracy.

Multi-channel solid-state LiDAR

LiDAR has obvious advantages at the roadside. The high cost however makes it hard to be used at the roadside on large scale. Thus the top priority for LiDAR suppliers is to cut down the application cost of roadside LiDARs.

High-resolution LiDAR performs much better in detection range and number of detected objects. For example, a 300-channel LiDAR offers a 150-meter detection range, while a 32-channel LiDAR can only perceive about 50 meters.

In addition, solid-state LiDAR is more applicable to the roadside that requires devices to work for a long time even without interruption. It remains superior in reliability and cost and is thus aligned more closely with the requirements for construction of 5G CVIS.

Innovusion

The Falcon AI was released at the end of 2022 as highly integrated ultra-long range AI LiDAR designed for CVIS and smart high-speed scenarios, with the longest detection distance of 500m and high-computing GPU module supporting various deep learning algorithms. It can greatly reduce the configuration requirements of edge computing and the complexity of system deployment.

Falcon AI, an integrated ultra-long-range AI LiDAR released in late 2022, targets vehicle-infrastructure cooperation and smart highway scenarios, with the longest detection range up to 500 meter. It integrates a high-compute GPU module to support various deep learning algorithms, which can greatly reduce the configuration requirements of edge computing and the complexity of system deployment.

The “Smart Road - Roadside Perception Industry Report, 2023” highlights the following:

  • Roadside perception industry (policies, standard formulation, market size, market structure, business model, etc.);
  • Key roadside perception technologies (LiDAR, radar, cameras, etc.) (status quo, trends, main suppliers and products), development trends of multi-sensor fusion for roadside perception, etc.;
  • Deployment cases of roadside perception hardware in main scenarios (smart highway, smart intersection, smart bus line, etc.);
  • Major roadside perception system integrators (summary on business lines, roadside perception integrated solutions, deployment of roadside perception hardware, etc.);
  • Major roadside perception hardware suppliers (product line layout, new product launch, etc.).

Table of Contents

1 Status Quo of Roadside Perception

  • 1.1 Requirements of Autonomous Driving for Roadside Perception
    • 1.1.1 The Development of Smart Roads Poses Higher Requirements for Roadside Perception
    • 1.1.2 The Development of Smart Roads Requires CVIS
    • 1.1.3 Construction Elements of CVIS-enabled Roads
    • 1.1.4 CVIS Roadside System (1)
    • 1.1.5 CVIS Roadside System (2)
    • 1.1.6 Dependence on Roadside Perception in the Development of CVIS
  • 1.2 Roadside Perception Development Policies and Standards
    • 1.2.1 The Five-year Action Plan for Accelerating the Construction of a Transportation Power (2023-2027) Was Released
    • 1.2.2 The Ministry of Industry and Information Technology of China Proposed Further Improvement in Connectivity Infrastructure Construction
    • 1.2.3 Levels of Road Intelligence
    • 1.2.4 Levels of Smart Highways in Hebei (1)
    • 1.2.5 Levels of Smart Highways in Hebei (2)
    • 1.2.6 The Latest Standard Dynamics in 2023: CVIS Roadside Infrastructure-Technical Requirements and Test Methods for LiDAR
    • 1.2.7 The Latest Standard Dynamics in 2023: Roadside Sensing System for Vehicle Infrastructure Cooperative System-Part 1: Technical Requirements
    • 1.2.8 Association Standard: Technical Requirements of Roadside Millimeter Wave Radar in Cooperative Vehicle Infrastructure System (1)
    • 1.2.9 Association Standard: Technical Requirements of Roadside Millimeter Wave Radar in Cooperative Vehicle Infrastructure System (2)
    • 1.2.10 Construction of Intelligent Roadside Standard System
  • 1.3 Intelligent Roadside Perception Market Size
    • 1.3.1 Market Size - Estimates and Assumptions
    • 1.3.2 Highway Roadside Perception Device Market Size, 2022-2026E (1)
    • 1.3.3 Highway Roadside Perception Device Market Size, 2022-2026E (2)
    • 1.3.4 Urban Intersection Perception Device Market Size, 2022-2026E (1)
    • 1.3.5 Urban Intersection Perception Device Market Size, 2022-2026E (2)
    • 1.3.6 China's Roadside Perception Market Size, 2022-2026E
  • 1.4 Intelligent Roadside Perception Industry Chain Pattern
    • 1.4.1 Top 10 Roadside Perception Integrated Solution Suppliers (1)
    • 1.4.2 Top 10 Roadside Perception Integrated Solution Suppliers (2)
    • 1.4.3 Top 10 Roadside Perception Integrated Solution Suppliers (3)
    • 1.4.4 Top 10 Roadside Radar-Video Integrated Solution Suppliers (1)
    • 1.4.5 Top 10 Roadside Radar-Video Integrated Solution Suppliers (2)
    • 1.4.6 Top 10 Roadside LiDAR Suppliers (1)
    • 1.4.7 Top 10 Roadside LiDAR Suppliers (2)
    • 1.4.8 Top 10 Roadside Radar Suppliers (1)
    • 1.4.9 Top 10 Roadside Radar Suppliers (2)
    • 1.4.10 Top 10 Roadside Camera Suppliers (1)
    • 1.4.11 Top 10 Roadside Camera Suppliers (2)
    • 1.4.12 Roadside Perception Product Layout of Major Suppliers (1)
    • 1.4.13 Roadside Perception Product Layout of Major Suppliers (2)
  • 1.5 Exploration of Roadside Perception Business Models
    • 1.5.1 Use "Vehicle- Road-Cloud Integrated" Solutions to Create a Commercial Closed Loop of Roadside Perception (1)
    • 1.5.2 Use "Vehicle- Road-Cloud Integrated" Solutions to Create a Commercial Closed Loop of Roadside Perception (2)
    • 1.5.3 Explore Different Profit Models for Cost Recovery
    • 1.5.4 The Future Operators in the Roadside Market May Be Changed from Governments to Companies

2 Key Technologies and Development Trends of Roadside Perception

  • 2.1 Key Technologies and Construction Difficulties of Roadside Perception
    • 2.1.1 Advantages and Disadvantages of Main Roadside Perception Devices
    • 2.1.2 Market Maturity of Main Roadside Perception Technologies
    • 2.1.3 Development Trends of Roadside Perception Technologies
  • 2.2 LiDAR Technology
    • 2.2.1 Technical Requirements for Roadside LiDAR
    • 2.2.2 Necessity of Deploying LiDAR on Roadside (1)
    • 2.2.3 Necessity of Deploying LiDAR on Roadside (2)
    • 2.2.4 Priority Application Scenarios of LiDAR on Roadside
    • 2.2.5 Market Opportunities for LiDAR on Roadside
    • 2.2.6 Roadside LiDAR Development Trend 1
    • 2.2.7 Roadside LiDAR Development Trend 2
    • 2.2.8 Roadside LiDAR Development Trend 3
    • 2.2.9 Roadside LiDAR Development Trend 4
    • 2.2.10 Cases
    • 2.2.11 Summary of Major Roadside LiDAR Suppliers and Products (1)
    • 2.2.12 Summary of Major Roadside LiDAR Suppliers and Products (2)
  • 2.2 Radar Technology
    • 2.3.1 Technical Requirements for Roadside Radar
    • 2.3.2 Roadside Radar Installation and Deployment
    • 2.3.3 Requirements of CVIS for Roadside Radar (1)
    • 2.3.4 Requirements of CVIS for Roadside Radar (2)
    • 2.3.5 Landscape of Roadside Radar Suppliers (1)
    • 2.3.6 Comparison between Major Suppliers in Products and Technologies (1)
    • 2.3.7 Comparison between Major Suppliers in Products and Technologies (2)
    • 2.3.8 Roadside Radar Technology Trends (1)
    • 2.3.9 Roadside Radar Technology Trends (2)
  • 2.4 Roadside Cameras
    • 2.4.1 Technical Requirements for Roadside Cameras
    • 2.4.2 Roadside Radar Supplier Landscape
    • 2.4.3 Comparison between Major Suppliers in Products (1)
    • 2.4.4 Comparison between Major Suppliers in Products (2)
    • 2.4.5 Roadside Camera Technology Trend 1
    • 2.4.6 Roadside Camera Technology Trend 2
    • 2.4.7 Roadside Camera Technology Trend 3
  • 2.5 Development Trend 1: Multi-sensor Perceptual Fusion
    • 2.5.1 Multi-dimensional Sensor Solutions Become the Development Trend (1)
    • 2.5.2 Multi-dimensional Sensor Solutions Become the Development Trend (2)
    • 2.5.3 Multi-dimensional Sensor Solutions Become the Development Trend (3)
    • 2.5.4 Advantages of Radar-Video Integration in Roadside Perception (1)
    • 2.5.5 Advantages of Radar-Video Integration in Roadside Perception (2)
    • 2.5.6 Growing Demand for Radar-Video Integration in Smart Road Projects
    • 2.5.7 Radar-Video Integration Market Participants (1)
    • 2.5.8 Radar-Video Integration Market Participants (2)
    • 2.5.9 Radar-Video Integration Form 1: Integration of Radar and Video
    • 2.5.10 Radar-Video Integration Form 1: Radar-Video Integration Technology Suppliers (1)
    • 2.5.11 Radar-Video Integration Form 1: Radar-Video Integration Technology Suppliers (2)
    • 2.5.12 Radar-Video Integration Form 2: Integration of LiDAR and Video
    • 2.5.13 Radar-Video Integration Form 2: LiDAR-Video Integration Technology Suppliers
    • 2.5.14 Latest Multi-sensor Fusion Cases
  • 2.6 Development Trend 2: Holographic and Global Perception Platform
    • 2.6.1 Build a Holographic and Global Perception Platform Based on Roadside Perception
    • 2.6.2 Holographic Perception Platform Technology (1)
    • 2.6.3 Holographic Perception Platform Technology (2)
    • 2.6.4 Holographic Perception Platform Technology (3)
    • 2.6.5 Global Holographic Deployment Cases

3 Roadside Perception Application Deployment Cases

  • 3.1 Exploration of Roadside Perception Application Scenarios
    • 3.1.5 Optimal Application Scenarios in the Early Stage - Highways
    • 3.1.2 Optimal Application Scenarios in the Early Stage - Urban Roads
    • 3.1.3 Optimal Application Scenarios in the Early Stage - Closed Campuses
    • 3.1.4 Roadside Perception Deployment of Smart Roads Should Follow the "Point-Line-Area" Principle
  • 3.2 Smart Highway Roadside Perception Application Cases
    • 3.2.1 Development of Autonomous Driving on Highways
    • 3.2.2 Smart Highway Business Model Exploration
    • 3.2.3 Principles for Deploying Smart Highway Roadside Perception Devices (1)
    • 3.2.4 Principles for Deploying Smart Highway Roadside Perception Devices (2)
    • 3.2.5 Smart Highway Construction Case 1: Hangzhou-Shaoxing-Ningbo Smart Highway in Zhejiang Province (1)
    • 3.2.6 Smart Highway Construction Case 1: Hangzhou-Shaoxing-Ningbo Smart Highway in Zhejiang Province (2)
    • 3.2.7 Smart Highway Construction Cases 1: Hangzhou-Shaoxing-Ningbo Smart Highway in Zhejiang Province (3)
    • 3.2.8 Smart Highway Construction Case 2: Changsha-Yiyang Expressway in Hunan Province
    • 3.2.9 Smart Highway Construction Case 3: Yanqing-Chongli Expressway in Hebei Province (1)
    • 3.2.10 Smart Highway Construction Case 3: Yanqing-Chongli Expressway in Hebei Province (2)
    • 3.2.11 Smart Highway Construction Case 4: Smart Highway on the Changshu Section of G524 (1)
    • 3.2.12 Smart Highway Construction Case 4: Smart Highway on the Changshu Section of G524 (2)
    • 3.2.13 Smart Highway Construction Case 5: Smart Section of Beijing-Taipei Expressway (1)
    • 3.2.14 Smart Highway Construction Case 5: Smart Section of Beijing-Taipei Expressway (2)
    • 3.2.15 Smart Highway Construction Case 5: Smart Section of Beijing-Taipei Expressway (3)
    • 3.2.16 Smart Highway Construction Case 6: Beijing-Xiong'an Expressway
    • 3.2.17 Smart Highway Construction Case 7: Rongcheng-Wuhai Expressway (1)
    • 3.2.18 Smart Highway Construction Case 8: Rongcheng-Wuhai Expressway (2)
    • 3.2.19 Smart Highway Construction Case 9: Smart Highway Deployment Scheme of Hunan Province (1)
    • 3.2.20 Smart Highway Construction Case 9: Smart Highway V2X Deployment Scheme of Hunan Province (2)
    • 3.2.21 Smart Highway Construction Case 10: Huzhou Section of West Double Line of Hangzhou Ring Expressway
    • 3.2.22 Smart Highway Construction Case 11: Beijing-Harbin Expressway Intelligent Project
  • 3.3 Application Cases of Roadside Perception at Smart Intersections
    • 3.3.1 Smart Intersections
    • 3.3.2 Roadside Perception Equipment Deployment at Smart Intersections (1)
    • 3.3.3 Roadside Perception Equipment Deployment at Smart Intersections (2)
    • 3.3.4 Smart Intersection Solution Trend 1: More LiDAR Applications
    • 3.3.5 LiDAR Application Case 1: Smart Intersections in Beijing Yizhuang (1)
    • 3.3.6 LiDAR Application Case 1: Smart Intersections in Beijing Yizhuang (2)
    • 3.3.7 LiDAR Application Case 2: Smart Intersection Solutions of Chuxiong City, Yunnan
    • 3.3.8 LiDAR Application Case 3: Smart Intersection Construction Solutions of Jiading District, Shanghai
    • 3.3.9 Smart Intersection Solution Trend 2: Radar-Video Integrated Technology Empowers Holographic Intersections
    • 3.3.10 Application Cases of Radar-Video Integration
    • 3.3.11 Smart Intersection Solution Trend 3: Flexible Mobile Integrated Perception Devices
    • 3.3.12 Mobile Equipment Cases
    • 3.3.13 Roadside Perception Hardware Deployment on Some Demonstration Roads (1)
    • 3.3.14 Roadside Perception Hardware Deployment on Some Demonstration Roads (2)
    • 3.3.15 Roadside Perception Hardware Deployment at Smart Intersections: Crossroads
    • 3.3.16 Roadside Perception Hardware Deployment at Smart Intersections: Long Straight Roads
  • 3.4 Smart Bus Roadside Perception Application Cases
    • 3.4.1 Roadside Perception Deployment of City Bus Lines
    • 3.4.2 Smart Buses in Dadong District, Shenyang (1)
    • 3.4.3 Smart Buses in Dadong District, Shenyang (2)
    • 3.4.4 Smart Buses in Dadong District, Shenyang (3)
    • 3.4.5 Roadside Perception Hardware for Smart Bus Project in Dadong District, Shenyang
    • 3.4.6 Xiong'an "5G + Smart Bus" Pilot Project (1)
    • 3.4.7 Xiong'an "5G + Smart Bus" Pilot Project (2)

4 Roadside Perception System Integrators

  • 4.1 Business Summary of Roadside Perception Solution Providers
    • 4.1.1 Summary of Huawei's Roadside Perception Solutions
    • 4.1.2 Summary of Baidu's Roadside Perception Solutions
  • 4.13 Summary of VanJee Technology's Roadside Perception Solutions
    • 4.1.4 Summary of CiDi's Roadside Perception Solutions
    • 4.1.5 Summary of Hikvision's Roadside Perception Solutions
    • 4.1.6 Summary of TransInfo Technology's Roadside Perception Solutions
    • 4.1.7 Summary of HIKAILINK's Roadside Perception Solutions
    • 4.1.8 Summary of LiangDao Intelligence's Roadside Perception Solutions
  • 4.2 Huawei
    • 4.2.1 Roadside Perception System Lineup (1)
    • 4.2.2 Roadside Perception System Lineup (2)
    • 4.2.3 Roadside Perception Portfolio
    • 4.2.4 Stereo Radar-Video Event All-In-One
    • 4.2.5 Release of 1000-meter-wide Radar-Video Fitting and Shooting Solution
    • 4.2.6 Holographic Intersection Solutions for Urban Roads
    • 4.2.7 Advantages of Holographic Intersection Solutions
    • 4.2.8 AI Ultralow Light Bayonet Cameras
    • 4.2.9 Holographic Road Network (1)
    • 4.2.10 Holographic Road Network (2)
    • 4.2.11 Application of Holographic Road Network
    • 4.2.12 CVIS Solutions
    • 4.2.13 Highway Video Cloud Connected Road Network Perception Basis for Highway Industry
    • 4.2.14 Good Hope Smart Highway Roadside Perception Solution
  • 4.3 Baidu
    • 4.3.1 Roadside Perception Portfolio
    • 4.3.2 Smart Highway Perception Portfolio
    • 4.3.3 Intelligent Connected Roadside Operating System (Zhilu OS) 1.0 (1)
    • 4.3.4 Intelligent Connected Roadside Operating System (Zhilu OS) 1.0 (2)
    • 4.3.5 Ecological Partners of Intelligent Connected Roadside Operating System (Zhilu OS) 1.0
    • 4.3.6 Object-level Vehicle-side Perception and Roadside Perception Integration Debuted in Apollo 6.0
    • 4.3.7 ACE Smart Intersection Solution
    • 4.3.8 Smart Highway CVIS Solutions
    • 4.3.9 Application of Roadside Perception Solutions
  • 4.4 TransInfo Technology
    • 4.4.1 Profile
    • 4.4.2 R&D Layout
    • 4.4.3 Roadside Devices
    • 4.4.4 Construction Modes of Roadside Facilities
    • 4.4.5 TransInfo-Alibaba Highway Solutions
    • 4.4.6 City-level Dynamic and Static Traffic Integrated Solutions
  • 4.5 Dahua Technology
    • 4.5.1 Profile
    • 4.5.2 Highway Video Surveillance Solutions
    • 4.5.3 Radar-Video All-in-One
  • 4.6 Hikailink
    • 4.6.1 Profile
    • 4.6.2 Roadside Perception Products (1)
    • 4.6.3 Roadside Perception Products (2)
    • 4.6.4 Smart Road Solutions for Intelligent Vehicles
    • 4.6.5 CVIS Solutions
    • 4.6.6 Roadside Perception Deployment Scheme for Highway Scenarios
    • 4.6.7 Application of Roadside Perception: L4 Autonomous Bus Lines in Fujian Province
  • 4.7 Hualu Yiyun
    • 4.7.1 Profile
    • 4.7.2 Main Roadside Products
    • 4.7.3 CVIS Solutions
  • 4.8 Gosuncn
    • 4.8.1 Profile
    • 4.8.2 Intelligent Transportation Layout
    • 4.8.3 Intelligent Roadside Perception Solutions
  • 4.9 ZTE
    • 4.9.1 Intelligent Transportation Business
    • 4.9.2 Intelligent Roadside Perception Integrated Solutions
    • 4.9.3 JETFLOW's Intelligent Transportation Research Model
    • 4.9.4 ZTE and China Mobile verified the New Integrated Telematics Architecture of the 5G Wireless Computing Network
  • 4.10 VanJee Technology
    • 4.10.1 Profile
    • 4.10.2 Roadside Perception Portfolio
    • 4.10.3 Next-generation Roadside LiDAR
    • 4.10.4 Parameters of Intelligent Roadside Devices
    • 4.10.5 Roadside Smart Base Stations
    • 4.10.6 Roadside 3D LiDAR
    • 4.10.7 Features of Roadside Perception Products
    • 4.10.8 Roadside Monitoring Status of Roadside 3D LiDAR
    • 4.10.9 V2X+3D LiDAR Intelligent Roadside Perception Solution
  • 4.11 CiDi (Changsha Intelligent Driving Institute) Ltd.
    • 4.11.1 Profile
    • 4.11.2 Intelligent Roadside Perception Devices
    • 4.11.3 Intelligent Roadside Terminal System
    • 4.11.4 Application of Roadside Perception: Smart Intersections
  • 4.12 NEBULA LINK
    • 4.12.1 Intelligent Holographic Intersection Perception System
    • 4.12.2 Application of Roadside Perception System
  • 4.13 Hikvision
    • 4.13.1 Intelligent Driving Industry Layout
    • 4.13.2 Intelligent Roadside Perception Devices
    • 4.13.3 Radar-Video Perception Devices (1)
    • 4.13.4 Radar-Video Perception Devices (2)
  • 4.14 JueFX Technology
    • 4.14.1 Roadside Perception Solutions
    • 4.14.2 Intelligent Architecture of Vehicle-Infrastructure Cooperation
    • 4.14.3 Roadside Fusion Perception System
    • 4.14.4 Application of Roadside Fusion Perception System: Ports
    • 4.14.5 Application of Roadside Fusion Perception System: Urban Roads
  • 4.15 LiangDao Intelligence
    • 4.15.1 Roadside Perception Portfolio
    • 4.15.2 Roadside Perception Products
    • 4.15.3 Reference Solution for Hardware Deployment of LDTelescope?
    • 4.15.4 Roadside Truth System Based on Radar-Video Technology
    • 4.15.5 Roadside Perception Smart Transportation Solutions
    • 4.15.6 Application of Roadside Perception
    • 4.15.7 Roadside Perception Deployment at Highway and Tunnels
  • 4.16 Institute of Deep Perception Technology (IDPT)
    • 4.16.1 CVIS Holographic Perception System Solution: Deep Sea-1
    • 4.16.2 Roadside Perception Radar
    • 4.16.3 Radar-Video All-In-One: Huihai-3 (1)
    • 4.16.4 Radar-Video All-In-One: Huihai-3 (2)
    • 4.16.5 Radar-Video All-In-One: Huihai-3 (3)
    • 4.16.6 Holographic Intersection Perception Solutions
  • 4.17 OriginalTek
    • 4.17.1 Profile
    • 4.17.2 Holographic Perception Solutions
    • 4.17.3 Radar-Video All-In-One

5 Roadside Perception Device Suppliers

  • 5.1 ZTITS
    • 5.1.1 Profile
    • 5.1.2 Roadside Perception Portfolio
    • 5.1.3 Product System
    • 5.1.4 Roadside Video Edge Computing Devices
  • 5.2 Uniview Technologies
    • 5.2.1 Roadside Camera Products
    • 5.2.2 Roadside Radar Series
    • 5.2.3 Radar-Video All-in-One
    • 5.2.4 Smart Highway Solutions (1)
    • 5.2.5 Smart Highway Solutions (2)
    • 5.2.6 Smart Intersection Solutions
  • 5.3 Hurys
    • 5.3.1 Profile
    • 5.3.2 Features of 4D Radar
    • 5.3.3 Features of Traffic Radar
    • 5.3.4 Features of Radar-Video All-In-One
    • 5.3.5 Intelligent Roadside Perception Solutions (1)
    • 5.3.6 Intelligent Roadside Perception Solutions (2)
    • 5.3.7 Intelligent Roadside Perception Solutions (3)
    • 5.3.8 Intelligent Roadside Perception Solutions (4)
  • 5.4 Sinoits
    • 5.4.1 Launch of Dual-spectrum Radar-Video All-In-One
    • 5.4.2 Application of Dual-spectrum Radar-Video All-In-One
  • 5.5 DeGuRoon
    • 5.5.1 Profile
    • 5.5.2 Roadside Perception Portfolio
    • 5.5.3 Roadside Cameras
    • 5.5.4 Radar-Video All-In-One
    • 5.5.5 Omni-directional Radar
    • 5.5.6 New Products: 4D radar
    • 5.5.7 New Products: Next-generation Omni-directional Radar-Video All-In-One
    • 5.5.8 New Products: The Fourth-generation Ultra-long-range Omni-directional Radar: 360S Series
    • 5.5.9 New Products: Multi-spectrum Composite Radar
    • 5.5.10 Application Cases of Roadside Perception Equipment
  • 5.6 Raysun
    • 5.6.1 Profile
    • 5.6.2 Roadside Perception Portfolio
    • 5.6.3 Parameters of Roadside Perception Products
    • 5.6.4 Radar-Video All-in-One
    • 5.6.5 4D Radar-Video All-in-One
    • 5.6.6 Advantages of Roadside Perception Solutions Based on Raysun 4D Radar-Video All-In-One
    • 5.6.7 V2X Holographic Road Surface Perception Solutions
    • 5.6.8 Application of Radar-Video Integrated Technology to Smart Highways
  • 5.7 TransMicrowave
    • 5.7.1 Intelligent Roadside Perception Devices (1)
    • 5.7.2 Intelligent Roadside Perception Devices (2)
    • 5.7.3 Roadside Bayonet Velocity Radar
  • 5.8 Muniu Technology
    • 5.8.1 Profile
    • 5.8.2 Core Competence
    • 5.8.3 Roadside Perception Portfolio
    • 5.8.4 Roadside Radar (1)
    • 5.8.5 Roadside Radar (2)
  • 5.9 HawkEye Technology
    • 5.9.1 Profile
    • 5.9.2 Roadside Perception Portfolio
    • 5.9.3 SDR Series High Performance Radar (1)
    • 5.9.4 SDR Series High Performance Radar (2)
    • 5.9.5 Technical Advantages
  • 5.10 SONDIT
    • 5.10.1 Profile
    • 5.10.2 Roadside Perception Portfolio
    • 5.10.3 Radar-Video All-in-One
    • 5.10.4 Radar
    • 5.10.5 Radar CVIS Roadside Perception System
  • 5.11 RACO Defense
    • 5.11.1 Roadside Perception Portfolio
    • 5.11.1 Multi-source Fusion Perception All-In-One
    • 5.11.3 Roadside Radar (1)
    • 5.11.4 Roadside Radar (2)
    • 5.11.5 Roadside Radar (3)
    • 5.11.6 Roadside Radar (4)
  • 5.12 Nanoradar
    • 5.12.1 Profile
    • 5.12.2 Roadside Perception Portfolio
    • 5.12.3 Strategy of Radar 321 for Lightweight Traffic Radar-Video All-in-One (1)
    • 5.12.4 Strategy of Radar 321 for Lightweight Traffic Radar-Video All-in-One (2)
    • 5.12.5 Radar MR76S (1)
    • 5.12.6 Radar MR76S (2)
  • 5.13 LeiShen Intelligent System
    • 5.13.1 Profile
    • 5.13.2 Roadside Perception Portfolio
    • 5.13.3 Radar-Video All-in-One
    • 5.13.4 LiDAR-enabled CVIS
    • 5.13.5 LiDAR-enabled CVIS Flow
    • 5.13.6 LiDAR-enabled CVIS Architecture
    • 5.13.7 LiDAR-enabled CVIS Hardware
    • 5.13.8 Application of CVIS Roadside Perception System
  • 5.14 RoboSense
    • 5.14.1 Roadside LiDAR
    • 5.14.2 Cooperation with CICT
    • 5.14.3 Cooperation with Tian-Net
  • 5.15 SMiTSense
    • 5.15.1 Intelligent Perception System Architecture
    • 5.15.2 Application of Roadside Intelligent Perception Products
  • 5.16 Benewake
    • 5.16.1 Roadside LiDAR
    • 5.16.2 Application of CVIS LiDAR
  • 5.17 Neuvition Technology
    • 5.17.1 Roadside LiDAR
    • 5.17.2 Smart Highway Solutions
  • 5.18 Others